Case-based maintenance : Structuring and incrementing the Case.

International audienceTo avoid performance degradation and maintain the quality of results obtained by the case-based reasoning (CBR) systems, maintenance becomes necessary, especially for those systems designed to operate over long periods and which must handle large numbers of cases. CBR systems cannot be preserved without scanning the case base. For this reason, the latter must undergo maintenance operations.The techniques of case base’s dimension optimization is the analog of instance reduction size methodology (in the machine learning community). This study links these techniques by presenting case-based maintenance in the framework of instance based reduction, and provides: first an overview of CBM studies, second, a novel method of structuring and updating the case base and finally an application of industrial case is presented.The structuring combines a categorization algorithm with a measure of competence CM based on competence and performance criteria. Since the case base must progress over time through the addition of new cases, an auto-increment algorithm is installed in order to dynamically ensure the structuring and the quality of a case base. The proposed method was evaluated through a case base from an industrial plant. In addition, an experimental study of the competence and the performance was undertaken on reference benchmarks. This study showed that the proposed method gives better results than the best methods currently found in the literature

Auto-incrémentation d'une base dysfonctionnelle de cas pour un système d'aide au diagnostic et à la réparation.

International audienceLe raisonnement à partir de cas est une méthode d'intelligence artificielle largement utilisée dans la résolution de problème de diagnostic technique. Après avoir mis en place un système de diagnostic et de réparation dédié à un système de transfert de palette, nous nous sommes intéressés à la maintenance de ce système et tout particulièrement à l'optimisation de la base de cas qui est au coeur du système et à sa remise à jour. Nous proposons dans cet article dans un premier temps d'optimiser la base de cas d'un système de raisonnement à partir de cas dédié au diagnostic de pannes et dans un deuxième temps d'enrichir la connaissance de ce système en rejoutant des cas de diagnostic non recensés d'une manière dynamique, sans altérer la structure de la base de cas mise en place. Ces 2 propositions ont été mises en place sur une plateforme de e-maintenance

Reutilization of diagnostic cases by adaptation of knowledge models.

International audienceThis paper deals with design of knowledge oriented diagnostic system. Two challenges are addressed. The first one concerns the elicitation of expert practice and the proposition of a methodology for developing four knowledge containers of case based reasoning system. The second one concerns the proposition of a general adaptation phase to reuse case solving diagnostic problems in a different context. In most cases, adaptation methods are application-specific and the challenge in this work is to make a general adaptation method for the field of industrial diagnostics applications. This paper is a contribution to fill this gap in the field of fault diagnostic and repair assistance of equipment. The proposed adaptation algorithm relies on hierarchy descriptors, an implied context model and dependencies between problems and solutions of the source cases. In addition, one can note that the first retrieved case is not necessarily the most adaptable case, and to take into account this report, an adaptation-guided retrieval step based on a similarity measure associated with an adaptation measure is realized on the diagnostic problem. These two measures allow selecting the most adaptable case among the retrieved cases. The two retrieval and adaptation phases are applied on real industrial system called Supervised industrial system of Transfer of pallets (SISTRE)

Case Base Maintenance Approach.

International audienceCase base Maintenance is an active Case Based Reasoning research area. The main stream focuses on the method for reducing the size of the case-base while maintaining case-base competence. This paper gives an overview of these works, and proposes a case deletion strategy based on competence criteria using a novel approach. The proposed method, even if inspired from existing literature, combines an algorithm with a Competence Metric (CM). A series of tests are conducted using two standards data-sets as well as a locally constructed one, on which, three Case Base Maintenance approaches were tested. This experimental study shows how this technique compares favourably to more traditional strategies across two standard data-sets

A methodology to conceive a case based system of industrial diagnosis.

International audienceThe objective of this paper is to address the diagnosis knowledge-oriented system in terms of artificial intelligence, particular by the Case-Based Reasoning (CBR) approach. Indeed, the use of CBR, which is an approach to problem solving and learning, in diagnosis goes back to a long time with the appearance of diagnostic support systems based on CBR. A diagnostic system by CBR implements an expertise-base composed of past experiences through which the origins of failure and the maintenance strategy are given according to a description of a specific situation of diagnostic. A study is made on the different diagnostic systems based on CBR. This study showed that there was no common methodology for building a CBR system. This design depends primarily on the case representation and knowledge models of the domain application. Consequently, this paper proposes a general design approach of a diagnostic system based on the CBR approach

Algorithme d'adaptation pour le diagnostic technique.

National audienceCet article présente un algorithme d'adaptation en raisonnement à partir de cas appliqué au diagnostic technique. La phase d'adaptation est considérée dans quelques travaux comme le coeur du processus du raisonnement à partir de cas. Il y a plusieurs axes de recherche concernant cette phase, nous nous intéressons aux démarches unificatrices. Dans ce cadre, nous proposons un algorithme d'adaptation pour le diagnostic technique traitant des cas ayant des valeurs de descripteurs modales. Cet algorithme prend appui sur la hiérarchie des descripteurs, leurs contextes ainsi que les dépendances entre le problème et la solution des cas sources. Une étude de la faisabilité de notre algorithme est faite sur un cas réel de diagnostic industriel. Trois cas de figures sont traités dans cette étude concernant les différentes valeurs des relations de dépendances et de l'appartenance aux classes hiérarchiques des descripteurs

Maintenance d'un système de raisonnement à partir de cas.

International audienceLa maintenance des systèmes de Raisonnement à partir de cas intéresse un certain nombre de travaux, dont nous dressons un état de l'art. Parmi les méthodes déployées ayant trait particulièrement à la maintenance de la base de cas, nous situons notre contribution dans la réduction de la base de cas, et plus particulièrement sur une stratégie de suppression de cas basée sur un critère : la compétence. Une mesure est proposée inspirée des travaux existant dans la littérature et est illustrée par un premier test fait sur une base de 69 cas

Competence-Preserving Case-Deletion Strategy for Case-Base Maintenance.

International audienceThe main goal of a Case-Based Reasoning (CBR) system is to provide criteria for evaluating the internal behavior and task efficiency of a particular system for a given initial case base and sequence of a solved problems. The choice of Case Base Maintenance (CBM) strategies is driven by the maintainer's performance goals for the system and by constraints on the system's design and the task environment. This paper gives an overview of CBM works and proposes a case deletion strategy based on a competence criterion using a novel approach. The proposed method combines an algorithm with a Competence Metric (CM). Series of tests are conducted using four standard data-sets as well as a locally constructed one, on which, three case base maintenance approaches will be tested and evaluated by competence and performance criteria. Thereafter competence and performance experimental study shows how this method compares favorably to more traditional methods

Evolution d'un système de raisonnement à partir de cas dédié au diagnostic industriel.

National audienceA partir de la démarche de conception d'un système de diagnostic définie par une base de cas et des modèles de connaissances générales, nous élaborons une base de cas constituée de prototypes d'expériences qui prenant appui sur les modèles de connaissances et de règles de décision, permet de réduire considérablement la base de cas initiale. Puis l'évolution de ce système de diagnostic est étudiée lorsque de nouveaux dysfonctionnements apparaissent sur l'équipement ou bien quand l'équipement est amené à évoluer suivant des spécifications de maintenance améliorative. Cette évolution aura des répercussions aussi bien sur la base de cas que sur les modèles du système. Nous proposons des étapes d'évolution du système ainsi qu'un algorithme d'insertion d'un nouveau cas dysfonctionnel dans la base de cas sans remettre en cause la qualité de la base. Cet algorithme exploite deux notions à savoir le recouvrement et l'atteignabilité

Adaptation-Guided retrieval for a diagnostic and repair help system dedicated to a pallets transfer.

International audienceIn this paper, we describe a CBR approach for failure diagnosis of a pallets transfer. Adaptation phase is the key problem of the case-based reasoning system conception. This paper is a contribution to fill this gap in the equipments diagnostic and repair help. Retrieval step guided by adaptation is proposed, as a result measures associated with an adaptation measure are proposed. These two measures will make it possible to select among the retrieved cases the most adaptable case. Then, an adaptation algorithm is proposed and will rely on a descriptors hierarchy, a context model as well as the dependences between problem and solution of the source cases. A feasibility study of the proposed algorithm is made on a real industrial diagnosis case. Three scenarios are treated in this study concerning various dependency relation values and belonging to the hierarchical classes of descriptors